.. _datasets:

Datasets

Torchvision provides many built-in datasets in the torchvision.datasets module, as well as utility classes for building your own datasets.

Built-in datasets

All datasets are subclasses of :class:torch.utils.data.Dataset i.e, they have __getitem__ and __len__ methods implemented. Hence, they can all be passed to a :class:torch.utils.data.DataLoader which can load multiple samples in parallel using torch.multiprocessing workers. For example: ::

imagenet_data = torchvision.datasets.ImageNet('path/to/imagenet_root/')
data_loader = torch.utils.data.DataLoader(imagenet_data,
                                          batch_size=4,
                                          shuffle=True,
                                          num_workers=args.nThreads)

.. currentmodule:: torchvision.datasets

All the datasets have almost similar API. They all have two common arguments: transform and target_transform to transform the input and target respectively. You can also create your own datasets using the provided :ref:base classes <base_classes_datasets>.

.. warning::

When a dataset object is created with ``download=True``, the files are first
downloaded and extracted in the root directory. This download logic is not
multi-process safe, so it may lead to conflicts / race conditions if it is
run within a distributed setting. In distributed mode, we recommend creating
a dummy dataset object to trigger the download logic *before* setting up
distributed mode.

Image classification


.. autosummary::
    :toctree: generated/
    :template: class_dataset.rst

    Caltech101
    Caltech256
    CelebA
    CIFAR10
    CIFAR100
    Country211
    DTD
    EMNIST
    EuroSAT
    FakeData
    FashionMNIST
    FER2013
    FGVCAircraft
    Flickr8k
    Flickr30k
    Flowers102
    Food101
    GTSRB
    INaturalist
    ImageNet
    Imagenette
    KMNIST
    LFWPeople
    LSUN
    MNIST
    Omniglot
    OxfordIIITPet
    Places365
    PCAM
    QMNIST
    RenderedSST2
    SEMEION
    SBU
    StanfordCars
    STL10
    SUN397
    SVHN
    USPS

Image detection or segmentation

.. autosummary:: :toctree: generated/ :template: class_dataset.rst

CocoDetection
CelebA
Cityscapes
Kitti
OxfordIIITPet
SBDataset
VOCSegmentation
VOCDetection
WIDERFace

Optical Flow


.. autosummary::
    :toctree: generated/
    :template: class_dataset.rst

    FlyingChairs
    FlyingThings3D
    HD1K
    KittiFlow
    Sintel

Stereo Matching

.. autosummary:: :toctree: generated/ :template: class_dataset.rst

CarlaStereo
Kitti2012Stereo
Kitti2015Stereo
CREStereo
FallingThingsStereo
SceneFlowStereo
SintelStereo
InStereo2k
ETH3DStereo
Middlebury2014Stereo

Image pairs


.. autosummary::
    :toctree: generated/
    :template: class_dataset.rst

    LFWPairs
    PhotoTour

Image captioning

.. autosummary:: :toctree: generated/ :template: class_dataset.rst

CocoCaptions

Video classification


.. autosummary::
    :toctree: generated/
    :template: class_dataset.rst

    HMDB51
    Kinetics
    UCF101

Video prediction

.. autosummary:: :toctree: generated/ :template: class_dataset.rst

MovingMNIST

.. _base_classes_datasets:

Base classes for custom datasets

.. autosummary:: :toctree: generated/ :template: class.rst

DatasetFolder
ImageFolder
VisionDataset

Transforms v2

.. autosummary:: :toctree: generated/ :template: function.rst

wrap_dataset_for_transforms_v2